What is it about?
Researchers at the University of Tokyo have presented a new method for characterizing the shape properties of nanoparticles. The new method overcomes a longstanding challenge in nanoparticle analysis that can be traced back to Einstein's time.
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Why is it important?
This research identifies an innovative method for evaluating nanoparticle shape using deep learning and expands the practical application of shape classification and its application to various industries. Shape classification will be put to practical use and its application will be expanded to various industries.
Perspectives
This method can be used to detect foreign particles, characterize nanoparticles, and ensure uniformity in a variety of industries. It is particularly promising for the characterization of biological nanoparticles such as extracellular vesicles.
Takanori Ichiki
The University of Tokyo
Read the Original
This page is a summary of: Analysis of Brownian motion trajectories of non-spherical nanoparticles using deep learning, APL Machine Learning, October 2023, American Institute of Physics,
DOI: 10.1063/5.0160979.
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